Notes
- ‘Support’ indicates agreement with question phrasing stated in plot
title: combining all relevant agreement levels from the question.
Setup
knitr::opts_chunk$set(echo = TRUE) # Set this to TRUE to show code.
knitr::opts_chunk$set(warning = FALSE, message = FALSE) # This hides some printed outputs
# Packages
library(tidyverse)
library(ggplot2)
library(rmarkdown)
library(scales)
library(ggrepel)
# Reading and merging
# Question files
for (i in 1:15) {
file_name <- paste0("question_", i, ".csv")
var_name <- paste0("question_", i)
assign(var_name, read.csv(file_name))
}
national_data <- read.csv("national_data_v1.csv")
national_data <- rename(national_data, ISO = iso2_code)
# Matching to national data
for (i in 1:15) {
question_var_name <- paste("question", i, sep = "_")
assign(question_var_name, head(left_join(get(question_var_name), national_data, by = "ISO"), -1))
}
# Creating gender gap variable
for (i in 1:15) {
question_var_name <- paste("question", i, sep = "_")
assign(question_var_name, mutate(get(question_var_name),
gender_gap = Female - Male
))
}
# Filter main
for (i in 1:15) {
question_var_name <- paste("question", i, sep = "_")
filtered_question_var_name <- paste("filtered_question", i, sep = "_")
temp_data <- get(question_var_name)
filtered_data <- temp_data[!is.na(temp_data$Overall), ]
assign(filtered_question_var_name, filtered_data)
}
Headline stats distribution
# Assuming 'filtered_questions' is a list of data frames where each data frame corresponds to a question's data
filtered_questions <- list(filtered_question_1, filtered_question_2, filtered_question_3, filtered_question_4, filtered_question_5, filtered_question_6, filtered_question_7, filtered_question_8, filtered_question_9, filtered_question_10, filtered_question_11, filtered_question_12, filtered_question_13, filtered_question_14, filtered_question_15)
# Titles for each plot
plot_titles <- c(
"Question 1 (think often about climate change): Distribution of support across countries",
"Question 2 (more worried c/w last year) : Distribution of support across countries",
"Question 3 (worried about next gen) : Distribution of support across countries",
"Question 4 (extreme weather - worse) : Distribution of support across countries",
"Question 5 (affected big decisions) : Distribution of support across countries",
"Question 6 (how well country addressing) : Distribution of support across countries",
"Question 7 (how well are big businesses addressing) : Distribution of support across countries",
"Question 8 (gov't has most impact addressing) : Distribution of support across countries",
"Question 9 (country should strengthen commitments) : Distribution of support across countries",
"Question 10 (country should replace fossil fuels more quickly) : Distribution of support across countries",
"Question 11 (country should protect and restore nature) : Distribution of support across countries",
"Question 12 (country should provide support to protect people at risk) : Distribution of support across countries",
"Question 13 (countries should work together) : Distribution of support across countries",
"Question 14 (rich countries should give more) : Distribution of support across countries",
"Question 15 (schools should teach more) : Distribution of support across countries"
)
# Function to create plot
create_plot <- function(data, title) {
ggplot(data, aes(x = Overall)) +
geom_histogram(binwidth = 0.5, fill = "#add8e6") +
scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10)),
axis.line.x = element_blank(),
axis.ticks.x = element_blank()
) +
labs(
title = title,
x = "Support",
y = "Frequency"
)
}
# Loop to create each plot
for (i in 1:length(filtered_questions)) {
print(create_plot(filtered_questions[[i]], plot_titles[i]))
}
Policy support vs CO2
# Question 9
ggplot(filtered_question_9, aes(x = co2_per_capita_owid, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst CO2 per capita",
x = "Annual CO2 per capita (tonnes per person)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = co2_per_capita_owid, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst CO2 per capita",
x = "Annual CO2 per capita (tonnes per person)",
y = "Question 10 support"
)
Policy support vs GDP pc
# Question 9
ggplot(filtered_question_9, aes(x = real_gdp_ppp_pc_cia, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst GDP per capita",
x = "GDP PPP per capita",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = real_gdp_ppp_pc_cia, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst GDP per capita",
x = "GDP PPP per capita",
y = "Question 10 support"
)
Policy support vs GDP PPP
# Question 9
ggplot(filtered_question_9, aes(x = real_gdp_ppp_cia, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst GDP",
x = "GDP PPP",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = real_gdp_ppp_cia, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = dollar_format(scaling = 0.001)) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst GDP",
x = "GDP PPP",
y = "Question 10 support"
)
Policy support vs oil production
# Question 9
ggplot(filtered_question_9, aes(x = oil_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst oil production",
x = "Oil production (terawatt-hours)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = oil_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst oil production",
x = "Oil production (terawatt-hours)",
y = "Question 10 support"
)
Policy support vs coal production
# Question 9
ggplot(filtered_question_9, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst coal production",
x = "Coal production (terawatt-hours)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production",
x = "Coal production (terawatt-hours)",
y = "Question 10 support"
)
Policy support vs subset of coal producers
# Top 10%
top_coal <- quantile(filtered_question_9$coal_production_ei, 0.80, na.rm = T)
filtered_question_9_coal <- subset(filtered_question_9, coal_production_ei >= top_coal)
filtered_question_10_coal <- subset(filtered_question_10, coal_production_ei >= top_coal)
filtered_question_9_coal_nochina <- subset(filtered_question_9_coal, Country != "China")
filtered_question_10_coal_nochina <- subset(filtered_question_10_coal, Country != "China")
# Question 9
ggplot(filtered_question_9_coal, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text_repel(aes(label = Country), nudge_y = 6, size = 3,
segment.color = 'grey50') +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst coal production: top 20% producers",
x = "Coal production (terawatt-hours)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10_coal, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text_repel(aes(label = Country), nudge_y = 6, size = 3,
segment.color = 'grey50') +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production: top 20% producers",
x = "Coal production (terawatt-hours)",
y = "Question 10 support"
)
# Without China
# Question 9
ggplot(filtered_question_9_coal_nochina, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text_repel(aes(label = Country), nudge_y = 6, size = 3,
segment.color = 'grey50') +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst coal production: top 20% producers w/o China",
x = "Coal production (terawatt-hours)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10_coal_nochina, aes(x = coal_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text_repel(aes(label = Country), nudge_y = 6, size = 3,
segment.color = 'grey50') +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 110), breaks = seq(0, 100, 25)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst coal production: top 20% producers w/o China",
x = "Coal production (terawatt-hours)",
y = "Question 10 support"
)
# Check significance
topcoal9_nochina <- lm(Overall ~ coal_production_ei, data = filtered_question_9_coal_nochina)
topcoal10_nochina <- lm(Overall ~ coal_production_ei, data = filtered_question_10_coal_nochina)
summary(topcoal9_nochina)
##
## Call:
## lm(formula = Overall ~ coal_production_ei, data = filtered_question_9_coal_nochina)
##
## Residuals:
## Min 1Q Median 3Q Max
## -15.391 -9.483 2.914 6.126 13.907
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 83.221056 4.484149 18.559 1.75e-08 ***
## coal_production_ei -0.002471 0.001905 -1.297 0.227
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 10.47 on 9 degrees of freedom
## Multiple R-squared: 0.1574, Adjusted R-squared: 0.06383
## F-statistic: 1.682 on 1 and 9 DF, p-value: 0.2269
summary(topcoal10_nochina)
##
## Call:
## lm(formula = Overall ~ coal_production_ei, data = filtered_question_10_coal_nochina)
##
## Residuals:
## Min 1Q Median 3Q Max
## -43.841 -3.836 -0.230 13.123 21.839
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 69.212859 8.810464 7.856 2.56e-05 ***
## coal_production_ei -0.003608 0.003743 -0.964 0.36
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 20.57 on 9 degrees of freedom
## Multiple R-squared: 0.09356, Adjusted R-squared: -0.007153
## F-statistic: 0.929 on 1 and 9 DF, p-value: 0.3603
Policy support vs gas production
# Question 9
ggplot(filtered_question_9, aes(x = gas_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst gas production",
x = "Gas production (terawatt-hours)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = gas_production_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = comma_format()) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst gas production",
x = "Gas production (terawatt-hours)",
y = "Question 10 support"
)
Policy support vs renewables
# Question 9
ggplot(filtered_question_9, aes(x = renewable_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_9$renewable_ei, na.rm = TRUE), max(filtered_question_9$renewable_ei, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst renewables",
x = "Renewables (share of energy consumption)",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = renewable_ei, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_10$renewable_ei, na.rm = TRUE), max(filtered_question_10$renewable_ei, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst renewables",
x = "Renewables (share of energy consumption)",
y = "Question 10 support"
)
HDI overall
filtered_question_1$hdi_undp <- as.numeric(filtered_question_1$hdi_undp)
filtered_question_2$hdi_undp <- as.numeric(filtered_question_2$hdi_undp)
filtered_question_3$hdi_undp <- as.numeric(filtered_question_3$hdi_undp)
filtered_question_4$hdi_undp <- as.numeric(filtered_question_4$hdi_undp)
filtered_question_5$hdi_undp <- as.numeric(filtered_question_5$hdi_undp)
filtered_question_6$hdi_undp <- as.numeric(filtered_question_6$hdi_undp)
filtered_question_7$hdi_undp <- as.numeric(filtered_question_7$hdi_undp)
filtered_question_8$hdi_undp <- as.numeric(filtered_question_8$hdi_undp)
filtered_question_9$hdi_undp <- as.numeric(filtered_question_9$hdi_undp)
filtered_question_10$hdi_undp <- as.numeric(filtered_question_10$hdi_undp)
filtered_question_11$hdi_undp <- as.numeric(filtered_question_11$hdi_undp)
filtered_question_12$hdi_undp <- as.numeric(filtered_question_12$hdi_undp)
filtered_question_13$hdi_undp <- as.numeric(filtered_question_13$hdi_undp)
filtered_question_14$hdi_undp <- as.numeric(filtered_question_14$hdi_undp)
filtered_question_15$hdi_undp <- as.numeric(filtered_question_15$hdi_undp)
filtered_questions <- list(
filtered_question_1, filtered_question_2, filtered_question_3,
filtered_question_4, filtered_question_5, filtered_question_6,
filtered_question_7, filtered_question_8, filtered_question_9,
filtered_question_10, filtered_question_11, filtered_question_12,
filtered_question_13, filtered_question_14, filtered_question_15
)
create_plot <- function(data, title) {
ggplot(data, aes(x = hdi_undp, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
scale_x_continuous(limits = c(min(data$hdi_undp, na.rm = TRUE), max(data$hdi_undp, na.rm = TRUE))) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = title,
x = "HDI",
y = paste("Support")
)
}
for (i in seq_along(filtered_questions)) {
print(create_plot(filtered_questions[[i]], plot_titles[i]))
}
HDI gender gap
# Question 3
ggplot(filtered_question_3, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
scale_x_continuous(limits = c(min(filtered_question_3$hdi_undp, na.rm = TRUE), max(filtered_question_3$hdi_undp, na.rm = TRUE))) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 3 (worried about next gen) against HDI gender gap",
x = "HDI",
y = "Question 3 gender gap (women over men)"
)
# Question 9
ggplot(filtered_question_9, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
scale_x_continuous(limits = c(min(filtered_question_9$hdi_undp, na.rm = TRUE), max(filtered_question_9$hdi_undp, na.rm = TRUE))) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst HDI gender gap",
x = "HDI",
y = "Question 9 gender gap (women over men)"
)
# Question 10
ggplot(filtered_question_10, aes(x = hdi_undp, y = gender_gap, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(-25, 25)) +
scale_x_continuous(limits = c(min(filtered_question_10$hdi_undp, na.rm = TRUE), max(filtered_question_10$hdi_undp, na.rm = TRUE))) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst HDI gender gap",
x = "HDI",
y = "Question 10 gender gap (women over men)"
)
Policy support vs Islam
# Question 9
ggplot(filtered_question_9, aes(x = islam_pew, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_9$islam_pew, na.rm = TRUE), max(filtered_question_9$islam_pew, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst Islam",
x = "Muslim pc of population",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = islam_pew, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(labels = function(x) paste0(x, "%"), limits = c(min(filtered_question_10$islam_pew, na.rm = TRUE), max(filtered_question_10$islam_pew, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Islam",
x = "Muslim pc of population",
y = "Question 10 support"
)
Experiences of climate change vs expression of experience
# Natural disasters
# Question 1
ggplot(filtered_question_1, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_1$natural_disasters_imf, na.rm = TRUE), max(filtered_question_1$natural_disasters_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 1 (think often about climate change)\nagainst natural disasters",
x = "Natural disasters yearly average 2017-2022",
y = "Question 1 support"
)
# Question 2
ggplot(filtered_question_2, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_2$natural_disasters_imf, na.rm = TRUE), max(filtered_question_2$natural_disasters_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 2 (more worried c/w last year)\nagainst natural disasters",
x = "Natural disasters yearly average 2017-2022",
y = "Question 2 support"
)
# Surface temp
# Question 1
ggplot(filtered_question_1, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_1$surface_temp_imf, na.rm = TRUE), max(filtered_question_1$surface_temp_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 1 (think often about climate change)\nagainst surface temp",
x = "Mean surface temp change 1961-2021",
y = "Question 1 support"
)
# Question 2
ggplot(filtered_question_2, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_2$surface_temp_imf, na.rm = TRUE), max(filtered_question_2$surface_temp_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 2 (more worried c/w last year)\nagainst surface temp",
x = "Mean surface temp change 1961-2021",
y = "Question 2 support"
)
Experiences of climate change vs policy support
# Natural disasters
# Question 9
ggplot(filtered_question_9, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$natural_disasters_imf, na.rm = TRUE), max(filtered_question_9$natural_disasters_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst natural disasters",
x = "Natural disasters yearly average 2017-2022",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$natural_disasters_imf, na.rm = TRUE), max(filtered_question_10$natural_disasters_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst natural disasters",
x = "Natural disasters yearly average 2017-2022",
y = "Question 10 support"
)
# Question 12
ggplot(filtered_question_12, aes(x = natural_disasters_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_12$natural_disasters_imf, na.rm = TRUE), max(filtered_question_12$natural_disasters_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 12 (country should provide support to protect people at risk)\nagainst natural disasters",
x = "Natural disasters yearly average 2017-2022",
y = "Question 12 support"
)
# Surface temp
# Question 9
ggplot(filtered_question_9, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$surface_temp_imf, na.rm = TRUE), max(filtered_question_9$surface_temp_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst surface temp",
x = "Mean surface temp change 1961-2021",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$surface_temp_imf, na.rm = TRUE), max(filtered_question_10$surface_temp_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst surface temp",
x = "Mean surface temp change 1961-2021",
y = "Question 10 support"
)
# Question 12
ggplot(filtered_question_12, aes(x = surface_temp_imf, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_12$surface_temp_imf, na.rm = TRUE), max(filtered_question_12$surface_temp_imf, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 12 (country should provide support to protect people at risk)\nagainst surface temp",
x = "Mean surface temp change 1961-2021",
y = "Question 12 support"
)
Regime type
# Question 6
ggplot(filtered_question_6, aes(x = electdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_6$electdem_vdem, na.rm = TRUE), max(filtered_question_6$electdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 6 (how well country addressing)\nagainst Electoral democracy",
x = "Electoral democracy score",
y = "Question 6 support"
)
ggplot(filtered_question_6, aes(x = libdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_6$libdem_vdem, na.rm = TRUE), max(filtered_question_6$libdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 6 (how well country addressing)\nagainst Liberal democracy",
x = "Liberal democracy score",
y = "Question 6 support"
)
ggplot(filtered_question_6, aes(x = participdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_6$participdem_vdem, na.rm = TRUE), max(filtered_question_6$participdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 6 (how well country addressing)\nagainst participatory democracy",
x = "Participatory democracy score",
y = "Question 6 support"
)
ggplot(filtered_question_6, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_6$delibdem_vdem, na.rm = TRUE), max(filtered_question_6$delibdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 6 (how well country addressing)\nagainst deliberative democracy",
x = "Deliberative democracy score",
y = "Question 6 support"
)
ggplot(filtered_question_6, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_6$egaldem_vdem, na.rm = TRUE), max(filtered_question_6$egaldem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 6 (how well country addressing)\nagainst egalitarian democracy",
x = "Egalitarian democracy score",
y = "Question 6 support"
)
# Question 9
ggplot(filtered_question_9, aes(x = electdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$electdem_vdem, na.rm = TRUE), max(filtered_question_9$electdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst Electoral democracy",
x = "Electoral democracy score",
y = "Question 9 support"
)
ggplot(filtered_question_9, aes(x = libdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$libdem_vdem, na.rm = TRUE), max(filtered_question_9$libdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst Liberal democracy",
x = "Liberal democracy score",
y = "Question 9 support"
)
ggplot(filtered_question_9, aes(x = participdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$participdem_vdem, na.rm = TRUE), max(filtered_question_9$participdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst participatory democracy",
x = "Participatory democracy score",
y = "Question 9 support"
)
ggplot(filtered_question_9, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$delibdem_vdem, na.rm = TRUE), max(filtered_question_9$delibdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst deliberative democracy",
x = "Deliberative democracy score",
y = "Question 9 support"
)
ggplot(filtered_question_9, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_9$egaldem_vdem, na.rm = TRUE), max(filtered_question_9$egaldem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 9 (country should strengthen commitments)\nagainst egalitarian democracy",
x = "Egalitarian democracy score",
y = "Question 9 support"
)
# Question 10
ggplot(filtered_question_10, aes(x = electdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$electdem_vdem, na.rm = TRUE), max(filtered_question_10$electdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Electoral democracy",
x = "Electoral democracy score",
y = "Question 10 support"
)
ggplot(filtered_question_10, aes(x = libdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$libdem_vdem, na.rm = TRUE), max(filtered_question_10$libdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst Liberal democracy",
x = "Liberal democracy score",
y = "Question 10 support"
)
ggplot(filtered_question_10, aes(x = participdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$participdem_vdem, na.rm = TRUE), max(filtered_question_10$participdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst participatory democracy",
x = "Participatory democracy score",
y = "Question 10 support"
)
ggplot(filtered_question_10, aes(x = delibdem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$delibdem_vdem, na.rm = TRUE), max(filtered_question_10$delibdem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst deliberative democracy",
x = "Deliberative democracy score",
y = "Question 10 support"
)
ggplot(filtered_question_10, aes(x = egaldem_vdem, y = Overall, colour = Region)) +
geom_point() +
geom_smooth(method = "lm", se = FALSE, colour = "black", size = 0.25) +
geom_text(aes(label = Country), nudge_y = 4, check_overlap = TRUE, size = 3) +
scale_x_continuous(limits = c(min(filtered_question_10$egaldem_vdem, na.rm = TRUE), max(filtered_question_10$egaldem_vdem, na.rm = TRUE))) +
scale_y_continuous(labels = function(x) paste0(x, "%"), limits = c(0, 100)) +
theme_minimal() +
theme(
plot.title = element_text(margin = margin(b = 20)),
legend.position = "bottom",
axis.title.x = element_text(margin = margin(t = 10)),
axis.title.y = element_text(margin = margin(r = 10))
) +
labs(
title = "Question 10 (country should replace fossil fuels more quickly)\nagainst egalitarian democracy",
x = "Egalitarian democracy score",
y = "Question 10 support"
)
